This paper describes the status of the ISocRob MSL roboticsoccer team as required by the RoboCup 2009 qualiﬁcation procedures.Since its previous participation in RoboCup, the ISocRob team has car-ried out signiﬁcant developments in various topics, the most relevantof which are presented here. These include self-localization, 3D objecttracking and cooperative object localization, motion control and rela-tional behaviors. A brief description of the hardware of the ISocRobrobots and of the software architecture adopted by the team is also in-cluded.

1996

We consider the estimation of local greylevel image structure in terms of a layered representation. This type of representation has recently been successfully used to segment various objects from clutter using either optical ow or stereo disparity information. We argue that the same type of representation is useful for greylevel data in that it allows for the estimation of properties for each of several different components without prior segmentation. Our emphasis in this paper is on the process used to extract such a layered representation from a given image In particular we consider a variant of the EM algorithm for the estimation of the layered model and consider a
novel technique for choosing the number of layers to use. We briefly consider the use of a simple version of this approach for image segmentation and suggest two potential applications to the ARK project

1996

Our goal is to understand the principles of Perception, Action and Learning in autonomous systems that successfully interact with complex environments and to use this understanding to design future systems